Hierarchical Task-Building-Based Multisource Adaptive Meta Transfer Learning for Cross-Domain Fault Diagnosis

Cross-domain fault diagnosis leverages knowledge from multiple source domains to improve diagnostic accuracy in target domain. However, existing methods align source and target domains either jointly or independently, often neglecting the distributional discrepancies among source domains, which hinders effective knowledge transfer. To address this issue, we proposes a hierarchical task-building-based multisource adaptive meta transfer learning (HTB-MSAMTL) framework. First, the semantic alignmen